Systems and methods for combining static and dynamic code analysis

ABSTRACT

A computer-implemented method for combining static and dynamic code analysis may include 1) identifying executable code that is to be analyzed to determine whether the executable code is capable of leaking sensitive data, 2) performing a static analysis of the executable code to identify one or more objects which the executable code may use to transfer sensitive data, the static analysis being performed by analyzing the executable code without executing the executable code, 3) using a result of the static analysis to tune a dynamic analysis to track the one or more objects identified during the static analysis, and 4) performing the dynamic analysis by, while the executable code is being executed, tracking the one or more objects identified during the static analysis to determine whether the executable code leaks sensitive data via the one or more objects. Various other methods, systems, and computer-readable media are also disclosed.

BACKGROUND

Traditional code analysis tools may implement either static or dynamicanalysis to evaluate code for compliance with data loss preventionpolicies. Each type of analysis has various advantages anddisadvantages. For example, dynamic code analysis may be able to detectleakage of sensitive data through network traffic and applicationprogramming interface call traces, but dynamic analysis may be resourceintensive and cannot always determine the original source of thesensitive data. Static analysis may be more efficient than dynamicanalysis and may be able to identify execution paths that can directlyresult in information leakage, but static analysis may not be able todetermine the fate of sensitive data that is written to local files,placed on the clipboard, or is otherwise made available viainter-process communication mechanisms.

Both static and dynamic analysis may be ineffective in detecting dataleaking in certain situations. For example, both static and dynamicanalysis may fail to detect data leakage that occurs as a result ofcomplex interactions between multiple applications or within a singleapplication. What is needed, therefore, is a more efficient andeffective mechanism for analyzing code to determine whether the code iscapable of leaking sensitive data.

SUMMARY

As will be described in greater detail below, the instant disclosuregenerally relates to systems and methods for combining static anddynamic code analysis. In one example, a computer-implemented method forcombining static and dynamic code analysis may include 1) identifyingexecutable code that is to be analyzed to determine whether theexecutable code is capable of leaking sensitive data, 2) performing astatic analysis of the executable code to identify one or more objectswhich the executable code may use to transfer sensitive data, the staticanalysis being performed by analyzing the executable code withoutexecuting the executable code, 3) using a result of the static analysisto tune a dynamic analysis to track the one or more objects identifiedduring the static analysis, and 4) performing the dynamic analysis by,while the executable code is being executed, tracking the one or moreobjects identified during the static analysis to determine whether theexecutable code leaks sensitive data via the one or more objects.

According to various embodiments, the executable code comprises a singlesoftware application and the one or more objects which the executablecode may use to transfer data comprise one or more storage locationsthat the single software application may write to and read from.Alternatively, the executable code may include a plurality of softwareapplications and the one or more objects into which the executable codemay transfer data comprise one or more inter-process communicationchannels used to communicate between applications in the plurality ofsoftware applications.

In certain embodiments, using the result of the static analysis to tunethe dynamic analysis may include instrumenting the executable code totrack access to the one or more objects identified during the staticanalysis. In such embodiments, using the result of the static analysisto tune the dynamic analysis to track the one or more objects identifiedduring the static analysis may include identifying one or moreapplication programming interfaces capable of accessing sensitive dataand identifying one or more code paths capable of leaking sensitivedata. Also, instrumenting the executable code may include hooking theone or more application programming interfaces capable of accessingsensitive data, and performing the dynamic analysis may includeactivating analysis within one or more application programming interfacehooks to analyze the one or more code paths capable of leaking sensitivedata.

According to at least one embodiment, the executable code may includeJAVA bytecode and/or DALVIK bytecode. In various embodiments,identifying the executable code may include identifying a first softwareprogram that is capable of accessing sensitive data and identifying asecond software program that is capable of transferring sensitive dataoutside the computing system, where the executable code comprise thefirst and second software programs.

In one embodiment, a system for implementing the above-described methodmay include 1) an identification module programmed to identifyexecutable code that is to be analyzed to determine whether theexecutable code is capable of leaking sensitive data, 2) a staticanalyzer programmed to perform a static analysis of the executable codeto identify one or more objects which the executable code may use totransfer sensitive data, the static analysis being performed byanalyzing the executable code without executing the executable code, 3)a tuning module programmed to use a result of the static analysis totune a dynamic analysis to track the one or more objects identifiedduring the static analysis, 4) a dynamic analyzer programmed to performthe dynamic analysis by, while the executable code is being executed,tracking the one or more objects identified during the static analysisto determine whether the executable code leaks sensitive data via theone or more objects, and 5) at least one computer processor configuredto execute the identification module, the static analyzer, the tuningmodule, and the dynamic analyzer.

In some examples, the above-described method may be encoded ascomputer-readable instructions on a computer-readable-storage medium.For example, a computer-readable-storage medium may include one or morecomputer-executable instructions that, when executed by at least oneprocessor of a computing device, may cause the computing device to 1)identify executable code that is to be analyzed to determine whether theexecutable code is capable of leaking sensitive data, 2) perform astatic analysis of the executable code to identify one or more objectswhich the executable code may use to transfer sensitive data, the staticanalysis being performed by analyzing the executable code withoutexecuting the executable code, 3) use a result of the static analysis totune a dynamic analysis to track the one or more objects identifiedduring the static analysis, and 4) perform the dynamic analysis by,while the executable code is being executed, tracking the one or moreobjects identified during the static analysis to determine whether theexecutable code leaks sensitive data via the one or more objects.

Features from any of the above-mentioned embodiments may be used incombination with one another in accordance with the general principlesdescribed herein. These and other embodiments, features, and advantageswill be more fully understood upon reading the following detaileddescription in conjunction with the accompanying drawings and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings illustrate a number of exemplary embodimentsand are a part of the specification. Together with the followingdescription, these drawings demonstrate and explain various principlesof the instant disclosure.

FIG. 1 is a block diagram of an exemplary system for combining staticand dynamic code analysis.

FIG. 2 is a block diagram of an exemplary system for combining staticand dynamic code analysis.

FIG. 3 is a flow diagram of an exemplary method for combining static anddynamic code analysis.

FIG. 4 is a block diagram of an exemplary computing system capable ofimplementing one or more of the embodiments described and/or illustratedherein.

FIG. 5 is a block diagram of an exemplary computing network capable ofimplementing one or more of the embodiments described and/or illustratedherein.

Throughout the drawings, identical reference characters and descriptionsindicate similar, but not necessarily identical, elements. While theexemplary embodiments described herein are susceptible to variousmodifications and alternative forms, specific embodiments have beenshown by way of example in the drawings and will be described in detailherein. However, the exemplary embodiments described herein are notintended to be limited to the particular forms disclosed. Rather, theinstant disclosure covers all modifications, equivalents, andalternatives falling within the scope of the appended claims.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

Embodiments of the instant disclosure may combine static and dynamicanalysis to analyze executable code to determine whether the executablecode is capable of leaking sensitive data. For example, the systems andmethods described herein may use static analysis to identify objectsinto which sensitive information can flow and may then tune a dynamicanalysis to monitor the flow of sensitive data into and out of theidentified objects. In this manner, the sensitive data may be trackedacross storage and retrieval cycles of one application and/or multipleapplications. The analysis systems and methods disclosed herein may beparticularly useful on code within mobile devices (e.g., DALVIC virtualmachines on ANDROID devices). Embodiments of the instant disclosure mayalso analyze code on various other types of systems and may providevarious other features and advantages.

The following will provide, with reference to FIGS. 1-2, detaileddescriptions of exemplary systems for combining static and dynamic codeanalysis. Detailed descriptions of corresponding computer-implementedmethods will also be provided in connection with FIG. 3. In addition,detailed descriptions of an exemplary computing system and networkarchitecture capable of implementing one or more of the embodimentsdescribed herein will be provided in connection with FIGS. 4 and 5,respectively.

FIG. 1 is a block diagram of an exemplary system 100 for combiningstatic and dynamic code analysis. As illustrated in this figure,exemplary system 100 may include one or more modules 102 for performingone or more tasks. For example, and as will be explained in greaterdetail below, exemplary system 100 may include an identification module104 programmed to identify executable code that is to be analyzed todetermine whether the executable code is capable of leaking sensitivedata. System 100 may also include a static analyzer 106 programmed toperform a static analysis of the executable code to identify one or moreobjects which the executable code may use to transfer sensitive data,the static analysis being performed by analyzing the executable codewithout executing the executable code.

In addition, and as will be described in greater detail below, exemplarysystem 100 may include a tuning module 108 programmed to use a result ofthe static analysis to tune a dynamic analysis to track the one or moreobjects identified during the static analysis. System 100 may alsoinclude a dynamic analyzer 110 programmed to perform the dynamicanalysis by, while the executable code is being executed, tracking theone or more objects identified during the static analysis to determinewhether the executable code leaks sensitive data via the one or moreobjects. Although illustrated as separate elements, one or more ofmodules 102 in FIG. 1 may represent portions of a single module orapplication.

In certain embodiments, one or more of modules 102 in FIG. 1 mayrepresent one or more software applications or programs that, whenexecuted by a computing device, may cause the computing device toperform one or more tasks. For example, and as will be described ingreater detail below, one or more of modules 102 may represent softwaremodules stored and configured to run on one or more computing devices,such as the devices illustrated in FIG. 2 (e.g., computing device 202and/or computing device 206), computing system 410 in FIG. 4, and/orportions of exemplary network architecture 500 in FIG. 5. One or more ofmodules 102 in FIG. 1 may also represent all or portions of one or morespecial-purpose computers configured to perform one or more tasks.

As illustrated in FIG. 1, exemplary system 100 may also include one ormore databases, such as database 120. In one example, database 120 maybe configured to store static analysis results 122 and/or dynamicanalysis results 124. Database 120 may represent portions of a singledatabase or computing device or a plurality of databases or computingdevices. For example, database 120 may represent a portion of computingdevice 202 in FIG. 2, computing system 410 in FIG. 4, and/or portions ofexemplary network architecture 500 in FIG. 5. Alternatively, database120 in FIG. 1 may represent one or more physically separate devicescapable of being accessed by a computing device, such as computingsystem 410 in FIG. 4, and/or portions of exemplary network architecture500 in FIG. 5.

Exemplary system 100 in FIG. 1 may be implemented in a variety of ways.For example, all or a portion of exemplary system 100 may representportions of exemplary system 200 in FIG. 2. As shown in FIG. 2, system200 may include a computing device 202 in communication with a computingdevice 206 via a network 204. Computing device 202 may include modules102 and database 120 for performing local analysis on softwareapplication 210. Modules 102 may additionally or alternatively performlocal analysis on multiple applications installed to computing device202 or may perform remote analysis on one or more applications installedto one or more remote computing devices, such as software applications212 and 214 on computing device 206.

In one embodiment, one or more of modules 102 from FIG. 1 may, whenexecuted by at least one processor of computing device 202, enablecomputing device 202 to combining static and dynamic code analysis toanalyze code to determine whether the code is capable of leakingsensitive data. For example, and as will be described in greater detailbelow, one or more of modules 102 may cause computing device 202 to 1)identify executable code that is to be analyzed to determine whether theexecutable code is capable of leaking sensitive data, 2) perform astatic analysis of the executable code to identify one or more objectswhich the executable code may use to transfer sensitive data, the staticanalysis being performed by analyzing the executable code withoutexecuting the executable code, 3) use a result of the static analysis totune a dynamic analysis to track the one or more objects identifiedduring the static analysis, and 4) perform the dynamic analysis by,while the executable code is being executed, tracking the one or moreobjects identified during the static analysis to determine whether theexecutable code leaks sensitive data via the one or more objects.

Computing devices 202 and 206 generally represents any type or form ofcomputing device capable of reading computer-executable instructions.Examples of computing devices 202 and 206 include, without limitation,laptops, tablets, desktops, servers, cellular phones, personal digitalassistants (PDAs), multimedia players, embedded systems, combinations ofone or more of the same, exemplary computing system 410 in FIG. 4, orany other suitable computing device.

Network 204 generally represents any medium or architecture capable offacilitating communication or data transfer. Examples of network 204include, without limitation, an intranet, a wide area network (WAN), alocal area network (LAN), a personal area network (PAN), the Internet,power line communications (PLC), a cellular network (e.g., a GSMNetwork), exemplary network architecture 500 in FIG. 5, or the like.Network 204 may facilitate communication or data transfer using wirelessor wired connections. In one embodiment, network 204 may facilitatecommunication between computing device 202 and computing device 206.

FIG. 3 is a flow diagram of an exemplary computer-implemented method 300for combining static and dynamic code analysis. The steps shown in FIG.3 may be performed by any suitable computer-executable code and/orcomputing system. In some embodiments, the steps shown in FIG. 3 may beperformed by one or more of the components of system 100 in FIG. 1,system 200 in FIG. 2, computing system 410 in FIG. 4, and/or portions ofexemplary network architecture 500 in FIG. 5.

At step 302 in FIG. 3, one or more of the systems described herein mayidentify executable code that is to be analyzed to determine whether theexecutable code is capable of leaking sensitive data. For example,identification module 104 in FIG. 1 (which may, as detailed above,represent a portion of computing device 202 in FIG. 2) may identifyexecutable code that is to be analyzed to determine whether theexecutable code is capable of leaking sensitive data. Identificationmodule 104 may identify executable code to be analyzed in any suitablemanner. For example, identification module 104 may identify executablecode to be analyzed during development of the executable code.Additionally or alternatively, identification module 104 may identifythe executable code as part of a process for evaluating the executablecode within a particular computing environment and/or to evaluate thecode for compliance with one or more data-loss-prevention policies whilethe code is running.

As used herein, the phrase “data loss prevention” may refer to atechnique for protecting sensitive information by applying one or morepolicies, rules, and/or heuristics to data within the bounds of a dataloss prevention system to determine the disposition of the data invarious scenarios. In some examples, a data loss prevention system maybe configured to prevent sensitive information from leaking (e.g., beingtransmitted outside the bounds of the system under uncontrolledcircumstances). Additionally or alternatively, a data loss preventionsystem may be configured to prevent sensitive information from beingmisused and/or insecurely stored. Embodiments of the instant disclosuremay be implemented as part of a data loss prevention system.

In some embodiments, identification module 104 may identify theexecutable code by identifying one or more software applications to beanalyzed. For example, identification module 104 may identify softwareapplication 210 on computing device 202, software application 212 oncomputing device 206, and/or software application 214 on computingdevice 206. Identification module 104 may identify a single softwareapplication for analysis in some embodiments, and in other embodimentsidentification module 104 may identify multiple software applicationsfor analysis. For example, identification module 104 may identify afirst software program that is capable of accessing sensitive data and asecond software program that is capable of transferring sensitive dataoutside a computing device. In this manner, identification module 104may identify software applications to analyze interactions between thesoftware applications.

As used herein, the phrase “executable code” generally refers to anytype or form of instructions capable of being executed by a computingdevice. In some embodiments, executable code may include JAVA bytecodeand/or DALVIC bytecode. Executable code may also include code programmedin any other language and/or formatted in any other format.

As used herein, the phrase “sensitive data” may refer to any data that auser and/or company would not want sent outside of a computing device orsystem without knowledge and/or permission of the user and/or company.Examples of sensitive information may include, without limitation, aname, a phone number, a device identifier, an email address, a contact,a browser history, a browser cookie, a phone history, a message history,location information (e.g., global positioning system information),financial information (e.g., credit card numbers, bank account numbers,etc.), confidential information, privileged information, personalinformation (e.g., a social security number, a driver's license number,etc.), sensitive corporate information (e.g., intellectual property,customer lists, product roadmaps, etc.), usage information, and/or anyother type of sensitive data.

As used herein, the phrase “outside a computing device” may refer to anylocation external to and/or apart from a computing device. For example,if data is exposed outside a computing device, the data may betransferred to a removable hard drive attached to the computing device,the data may be transferred over a network to which the computing deviceis connected, the data may be displayed or otherwise provided on aninput/output device connected to the computing device, and/or the datamay be exposed in any other manner.

At step 304 in FIG. 3, one or more of the systems described herein mayperform a static analysis of the executable code to identify one or moreobjects which the executable code may use to transfer sensitive data.For example, static analyzer 106 in FIG. 1 (which may, as detailedabove, represent a portion of computing device 202 in FIG. 2) mayperform a static analysis of the software application 210 to identifyone or more objects which software application may use to transfersensitive data.

As used herein, the phrase “static analysis” generally refers to anyanalysis of code that is performed without actually executing anyinstructions of the code. In other words, static analysis may analyzethe text of executable code to derive properties of the code's executionwhile the code is static (i.e., not running). In some embodiments,static analysis may involve data-flow analysis to gather informationabout the executable code. In a data-flow analysis, static analyzer 106may use a program's control flow graph to determine parts of a programto which a particular value assigned to a variable might propagate.Static analyzer 106 may also implement data-flow analysis using anysuitable algorithm and/or heuristic.

As noted, static analyzer 106 may perform a static analysis of theexecutable code to identify objects which the executable code may use totransfer sensitive data. The executable code may use one or more ofvarious types of objects to transfer sensitive data. For example,executable code may use inter-process communication channels (e.g.,named pipes, message passing such as broadcasted intents,synchronization, shared memory, copy and paste functions, clipboards,remote procedure calls, etc.) to transfer sensitive data. Other examplesof objects used to transfer sensitive data include APIs (e.g., dataaccess APIs programmed to provide access to sensitive information, datatransfer APIs programmed to send information outside a computing device,etc.), and/or storage locations (e.g., files, databases, DALVIC bytecodecontent providers, etc.).

In some embodiments, static analyzer 106 may perform a static analysison a single software application. In such embodiments, static analyzer106 may identify objects to which the executable code (i.e., the singlesoftware application) may write, read, and/or transfer sensitive data.For example, if a software application is capable of writing sensitivedata to a file and is also capable of exporting the file, staticanalyzer 106 may identify the file as an object capable of leakingsensitive data.

As noted above, static analyzer 106 may also analyze a plurality ofsoftware applications. In such embodiments, static analyzer 106 mayidentify one or more storage locations that each software application inthe plurality may access and/or may identify inter-process communicationmechanisms that may transfer sensitive data between two or more softwareapplications. For example, static analyzer 106 may determine that twoprograms share memory to which sensitive data may be stored.

At step 306 in FIG. 3, one or more of the systems described herein mayuse a result of the static analysis to tune a dynamic analysis to trackthe one or more objects identified during the static analysis. Forexample, tuning module 108 (which may, as detailed above, represent aportion of computing device 202 in FIG. 2) may use a result of thestatic analysis to tune a dynamic analysis to track one or more objectsidentified during the static analysis.

Tuning module 108 may use the result of the static analysis to tune adynamic analysis in any suitable manner. For example, tuning module 108may use the objects identified during static analysis to tune a dynamicanalysis to track, monitor, and/or otherwise analyze the objectsidentified during the static analysis.

In some embodiments, tuning module 108 may use the result of the staticanalysis to tune the dynamic analysis by instrumenting the executablecode to track access to the one or more objects identified during thestatic analysis. Tuning module 108 may instrument the executable code byinserting analysis code into the executable code inline, by using one ormore external routines, and/or in any other suitable manner. Forexample, tuning module 108 may use static binary instrumentation toinstrument the executable code before the code is run. Tuning module 108may also use dynamic binary instrumentation to inject analysis code intothe executable code while the executable code is running.

In one example of instrumenting the executable code, tuning module 108may identify one or more APIs capable of accessing sensitive data (e.g.,reading, writing, and/or transferring sensitive data). Tuning module 108may also identify one or more code paths capable of leaking sensitivedata. In such embodiments, tuning module 108 may instrument theexecutable code by hooking the one or more APIs capable of accessingsensitive data such that, when the dynamic analysis is performed, thedynamic analysis may activate analysis within one or more API hooks toanalyze the one or more code paths capable of leaking sensitive data.

Tuning module 108 may additionally or alternatively instrument theexecutable code to watch data written to and read from a storagelocation identified during the static analysis, to track sensitive datapassed between programs using other inter-process communicationchannels, and/or in any other manner.

At step 308 in FIG. 3, one or more of the systems described herein mayperform the dynamic analysis by, while the executable code is beingexecuted, tracking the one or more objects identified during the staticanalysis to determine whether the executable code leaks sensitive datavia the one or more objects. For example, dynamic analyzer 110 in FIG. 1(which may, as detailed above, represent a portion of computing device202 in FIG. 2) may perform the dynamic analysis by, while softwareapplication 210 is being executed, tracking the one or more objectsidentified during the static analysis to determine whether softwareapplication 210 leaks sensitive data via the one or more objects.

Dynamic analyzer 110 may perform the dynamic analysis in any suitablemanner. For example, dynamic analyzer 110 may monitor code pathsidentified by static analyzer 106, may monitor APIs identified by staticanalyzer 106, may monitor files identified by static analyzer 106, mayidentify and analyze inter-process communication channels identified bystatic analyzer 106, and/or may perform any other suitable analysis ofthe executable code based on information obtained by static analyzer106.

Dynamic analyzer 110 may perform the dynamic analysis in a variety ofcontexts. For example, dynamic analyzer 110 may be used to identifyindividual applications that may compromise sensitive data. As anotherexample, dynamic analyzer 110 may analyze a set of applications todetermine whether any installed combination of applications results in arisk of sensitive data being leaked. If a single application orcombination of applications results in risk of sensitive data beingleaked, the systems described herein may warn consumers that installingthe application(s) may present a privacy risk.

In some embodiments, dynamic analyzer 110 may perform the dynamicanalysis while a computing system is in use to detect attempts by theexecutable code to leak sensitive data. If dynamic analyzer 110 detectsan attempt to leak sensitive data, a data loss prevention system mayperform a security action with respect to the sensitive data.

A data loss prevention system may perform a security action in a varietyof ways. For example, the data loss prevention system may perform thesecurity action by logging the attempt to leak sensitive data outside ofa computing device. In the log, the data loss prevention system mayidentify the application that attempted to leak sensitive data, how theapplication accessed or used sensitive data, and/or the destination towhich the application attempted to leak sensitive data. The data lossprevention system may also store the log to a log file, a database,and/or to a memory location on a computing device. The data lossprevention system may further send the log to a remote tracking server,to an administrator, and/or to any other destination.

In one embodiment, the data loss prevention system may perform thesecurity action by notifying a user of a computing device of the attemptto leak sensitive data outside of the computing device. For example, thedata loss prevention system may present a notification, to the user ofthe computing device, indicating that the attempt to leak sensitive datawas detected. The data loss prevention system may also enable the userof the computing device to prevent the leak of sensitive data (e.g., byquerying the user about whether to allow the information to betransmitted outside of a computing device).

In another embodiment, the data loss prevention system may perform thesecurity action by notifying a third party of the attempt to leaksensitive data outside of a computing device. For example, the data lossprevention system may notify an operating system provider, a securityvendor, an application store provider, and/or a cellular provider aboutthe attempt to leak sensitive data.

In some embodiments, the data loss prevention system may perform thesecurity action by preventing the attempt to leak sensitive data outsideof a computing device. For example, the data loss prevention system mayprevent the attempt, by the executable code, to leak sensitive data byquarantining the executable code, by removing the executable code from acomputing device, by preventing the executable code from sending anyinformation outside of a computing device, and/or by preventing theexecutable code from sending any information outside of a computingdevice that comprises sensitive data.

FIG. 4 is a block diagram of an exemplary computing system 410 capableof implementing one or more of the embodiments described and/orillustrated herein. For example, all or a portion of computing system410 may perform and/or be a means for performing, either alone or incombination with other elements, one or more of the instrumenting,performing, using, and identifying steps described herein. All or aportion of computing system 410 may also perform and/or be a means forperforming any other steps, methods, or processes described and/orillustrated herein.

Computing system 410 broadly represents any single or multi-processorcomputing device or system capable of executing computer-readableinstructions. Examples of computing system 410 include, withoutlimitation, workstations, laptops, client-side terminals, servers,distributed computing systems, handheld devices, or any other computingsystem or device. In its most basic configuration, computing system 410may include at least one processor 414 and a system memory 416.

Processor 414 generally represents any type or form of processing unitcapable of processing data or interpreting and executing instructions.In certain embodiments, processor 414 may receive instructions from asoftware application or module. These instructions may cause processor414 to perform the functions of one or more of the exemplary embodimentsdescribed and/or illustrated herein.

System memory 416 generally represents any type or form of volatile ornon-volatile storage device or medium capable of storing data and/orother computer-readable instructions. Examples of system memory 416include, without limitation, random access memory (RAM), read onlymemory (ROM), flash memory, or any other suitable memory device.Although not required, in certain embodiments computing system 410 mayinclude both a volatile memory unit (such as, for example, system memory416) and a non-volatile storage device (such as, for example, primarystorage device 432, as described in detail below). In one example, oneor more of modules 102 from FIG. 1 may be loaded into system memory 416.

In certain embodiments, exemplary computing system 410 may also includeone or more components or elements in addition to processor 414 andsystem memory 416. For example, as illustrated in FIG. 4, computingsystem 410 may include a memory controller 418, an Input/Output (I/O)controller 420, and a communication interface 422, each of which may beinterconnected via a communication infrastructure 412. Communicationinfrastructure 412 generally represents any type or form ofinfrastructure capable of facilitating communication between one or morecomponents of a computing device. Examples of communicationinfrastructure 412 include, without limitation, a communication bus(such as an ISA, PCI, PCIe, or similar bus) and a network.

Memory controller 418 generally represents any type or form of devicecapable of handling memory or data or controlling communication betweenone or more components of computing system 410. For example, in certainembodiments memory controller 418 may control communication betweenprocessor 414, system memory 416, and I/O controller 420 viacommunication infrastructure 412.

I/O controller 420 generally represents any type or form of modulecapable of coordinating and/or controlling the input and outputfunctions of a computing device. For example, in certain embodiments I/Ocontroller 420 may control or facilitate transfer of data between one ormore elements of computing system 410, such as processor 414, systemmemory 416, communication interface 422, display adapter 426, inputinterface 430, and storage interface 434.

Communication interface 422 broadly represents any type or form ofcommunication device or adapter capable of facilitating communicationbetween exemplary computing system 410 and one or more additionaldevices. For example, in certain embodiments communication interface 422may facilitate communication between computing system 410 and a privateor public network including additional computing systems. Examples ofcommunication interface 422 include, without limitation, a wired networkinterface (such as a network interface card), a wireless networkinterface (such as a wireless network interface card), a modem, and anyother suitable interface. In at least one embodiment, communicationinterface 422 may provide a direct connection to a remote server via adirect link to a network, such as the Internet. Communication interface422 may also indirectly provide such a connection through, for example,a local area network (such as an Ethernet network), a personal areanetwork, a telephone or cable network, a cellular telephone connection,a satellite data connection, or any other suitable connection.

In certain embodiments, communication interface 422 may also represent ahost adapter configured to facilitate communication between computingsystem 410 and one or more additional network or storage devices via anexternal bus or communications channel. Examples of host adaptersinclude, without limitation, SCSI host adapters, USB host adapters, IEEE1394 host adapters, SATA and eSATA host adapters, ATA and PATA hostadapters, Fibre Channel interface adapters, Ethernet adapters, or thelike. Communication interface 422 may also allow computing system 410 toengage in distributed or remote computing. For example, communicationinterface 422 may receive instructions from a remote device or sendinstructions to a remote device for execution.

As illustrated in FIG. 4, computing system 410 may also include at leastone display device 424 coupled to communication infrastructure 412 via adisplay adapter 426. Display device 424 generally represents any type orform of device capable of visually displaying information forwarded bydisplay adapter 426. Similarly, display adapter 426 generally representsany type or form of device configured to forward graphics, text, andother data from communication infrastructure 412 (or from a framebuffer, as known in the art) for display on display device 424.

As illustrated in FIG. 4, exemplary computing system 410 may alsoinclude at least one input device 428 coupled to communicationinfrastructure 412 via an input interface 430. Input device 428generally represents any type or form of input device capable ofproviding input, either computer or human generated, to exemplarycomputing system 410. Examples of input device 428 include, withoutlimitation, a keyboard, a pointing device, a speech recognition device,or any other input device.

As illustrated in FIG. 4, exemplary computing system 410 may alsoinclude a primary storage device 432 and a backup storage device 433coupled to communication infrastructure 412 via a storage interface 434.Storage devices 432 and 433 generally represent any type or form ofstorage device or medium capable of storing data and/or othercomputer-readable instructions. For example, storage devices 432 and 433may be a magnetic disk drive (e.g., a so-called hard drive), a solidstate drive, a floppy disk drive, a magnetic tape drive, an optical diskdrive, a flash drive, or the like. Storage interface 434 generallyrepresents any type or form of interface or device for transferring databetween storage devices 432 and 433 and other components of computingsystem 410. In one example, database 120 from FIG. 1 may be stored inprimary storage device 432.

In certain embodiments, storage devices 432 and 433 may be configured toread from and/or write to a removable storage unit configured to storecomputer software, data, or other computer-readable information.Examples of suitable removable storage units include, withoutlimitation, a floppy disk, a magnetic tape, an optical disk, a flashmemory device, or the like. Storage devices 432 and 433 may also includeother similar structures or devices for allowing computer software,data, or other computer-readable instructions to be loaded intocomputing system 410. For example, storage devices 432 and 433 may beconfigured to read and write software, data, or other computer-readableinformation. Storage devices 432 and 433 may also be a part of computingsystem 410 or may be a separate device accessed through other interfacesystems.

Many other devices or subsystems may be connected to computing system410. Conversely, all of the components and devices illustrated in FIG. 4need not be present to practice the embodiments described and/orillustrated herein. The devices and subsystems referenced above may alsobe interconnected in different ways from that shown in FIG. 4. Computingsystem 410 may also employ any number of software, firmware, and/orhardware configurations. For example, one or more of the exemplaryembodiments disclosed herein may be encoded as a computer program (alsoreferred to as computer software, software applications,computer-readable instructions, or computer control logic) on acomputer-readable-storage medium. The phrase “computer-readable-storagemedium” generally refers to any form of device, carrier, or mediumcapable of storing or carrying computer-readable instructions. Examplesof computer-readable-storage media include, without limitation,transmission-type media, such as carrier waves, and non-transitory-typemedia, such as magnetic-storage media (e.g., hard disk drives and floppydisks), optical-storage media (e.g., CD- or DVD-ROMs),electronic-storage media (e.g., solid-state drives and flash media), andother distribution systems.

The computer-readable-storage medium containing the computer program maybe loaded into computing system 410. All or a portion of the computerprogram stored on the computer-readable-storage medium may then bestored in system memory 416 and/or various portions of storage devices432 and 433. When executed by processor 414, a computer program loadedinto computing system 410 may cause processor 414 to perform and/or be ameans for performing the functions of one or more of the exemplaryembodiments described and/or illustrated herein. Additionally oralternatively, one or more of the exemplary embodiments described and/orillustrated herein may be implemented in firmware and/or hardware. Forexample, computing system 410 may be configured as an applicationspecific integrated circuit (ASIC) adapted to implement one or more ofthe exemplary embodiments disclosed herein.

FIG. 5 is a block diagram of an exemplary network architecture 500 inwhich client systems 510, 520, and 530 and servers 540 and 545 may becoupled to a network 550. As detailed above, all or a portion of networkarchitecture 500 may perform and/or be a means for performing, eitheralone or in combination with other elements, one or more of theinstrumenting, performing, using, and identifying steps disclosedherein. All or a portion of network architecture 500 may also be used toperform and/or be a means for performing other steps and features setforth in the instant disclosure.

Client systems 510, 520, and 530 generally represent any type or form ofcomputing device or system, such as exemplary computing system 410 inFIG. 4. Similarly, servers 540 and 545 generally represent computingdevices or systems, such as application servers or database servers,configured to provide various database services and/or run certainsoftware applications. Network 550 generally represents anytelecommunication or computer network including, for example, anintranet, a wide area network (WAN), a local area network (LAN), apersonal area network (PAN), or the Internet. In one example, clientsystems 510, 520, and/or 530 and/or servers 540 and/or 545 may includeall or a portion of system 100 from FIG. 1.

As illustrated in FIG. 5, one or more storage devices 560(1)-(N) may bedirectly attached to server 540. Similarly, one or more storage devices570(1)-(N) may be directly attached to server 545. Storage devices560(1)-(N) and storage devices 570(1)-(N) generally represent any typeor form of storage device or medium capable of storing data and/or othercomputer-readable instructions. In certain embodiments, storage devices560(1)-(N) and storage devices 570(1)-(N) may represent network-attachedstorage (NAS) devices configured to communicate with servers 540 and 545using various protocols, such as NFS, SMB, or CIFS.

Servers 540 and 545 may also be connected to a storage area network(SAN) fabric 580. SAN fabric 580 generally represents any type or formof computer network or architecture capable of facilitatingcommunication between a plurality of storage devices. SAN fabric 580 mayfacilitate communication between servers 540 and 545 and a plurality ofstorage devices 590(1)-(N) and/or an intelligent storage array 595. SANfabric 580 may also facilitate, via network 550 and servers 540 and 545,communication between client systems 510, 520, and 530 and storagedevices 590(1)-(N) and/or intelligent storage array 595 in such a mannerthat devices 590(1)-(N) and array 595 appear as locally attached devicesto client systems 510, 520, and 530. As with storage devices 560(1)-(N)and storage devices 570(1)-(N), storage devices 590(1)-(N) andintelligent storage array 595 generally represent any type or form ofstorage device or medium capable of storing data and/or othercomputer-readable instructions.

In certain embodiments, and with reference to exemplary computing system410 of FIG. 4, a communication interface, such as communicationinterface 422 in FIG. 4, may be used to provide connectivity betweeneach client system 510, 520, and 530 and network 550. Client systems510, 520, and 530 may be able to access information on server 540 or 545using, for example, a web browser or other client software. Suchsoftware may allow client systems 510, 520, and 530 to access datahosted by server 540, server 545, storage devices 560(1)-(N), storagedevices 570(1)-(N), storage devices 590(1)-(N), or intelligent storagearray 595. Although FIG. 5 depicts the use of a network (such as theInternet) for exchanging data, the embodiments described and/orillustrated herein are not limited to the Internet or any particularnetwork-based environment.

In at least one embodiment, all or a portion of one or more of theexemplary embodiments disclosed herein may be encoded as a computerprogram and loaded onto and executed by server 540, server 545, storagedevices 560(1)-(N), storage devices 570(1)-(N), storage devices590(1)-(N), intelligent storage array 595, or any combination thereof.All or a portion of one or more of the exemplary embodiments disclosedherein may also be encoded as a computer program, stored in server 540,run by server 545, and distributed to client systems 510, 520, and 530over network 550.

As detailed above, computing system 410 and/or one or more components ofnetwork architecture 500 may perform and/or be a means for performing,either alone or in combination with other elements, one or more steps ofan exemplary method for combining static and dynamic code analysis.

While the foregoing disclosure sets forth various embodiments usingspecific block diagrams, flowcharts, and examples, each block diagramcomponent, flowchart step, operation, and/or component described and/orillustrated herein may be implemented, individually and/or collectively,using a wide range of hardware, software, or firmware (or anycombination thereof) configurations. In addition, any disclosure ofcomponents contained within other components should be consideredexemplary in nature since many other architectures can be implemented toachieve the same functionality.

In some examples, all or a portion of exemplary system 100 in FIG. 1 mayrepresent portions of a cloud-computing or network-based environment.Cloud-computing environments may provide various services andapplications via the Internet. These cloud-based services (e.g.,software as a service, platform as a service, infrastructure as aservice, etc.) may be accessible through a web browser or other remoteinterface. Various functions described herein may be provided through aremote desktop environment or any other cloud-based computingenvironment.

The process parameters and sequence of steps described and/orillustrated herein are given by way of example only and can be varied asdesired. For example, while the steps illustrated and/or describedherein may be shown or discussed in a particular order, these steps donot necessarily need to be performed in the order illustrated ordiscussed. The various exemplary methods described and/or illustratedherein may also omit one or more of the steps described or illustratedherein or include additional steps in addition to those disclosed.

While various embodiments have been described and/or illustrated hereinin the context of fully functional computing systems, one or more ofthese exemplary embodiments may be distributed as a program product in avariety of forms, regardless of the particular type ofcomputer-readable-storage media used to actually carry out thedistribution. The embodiments disclosed herein may also be implementedusing software modules that perform certain tasks. These softwaremodules may include script, batch, or other executable files that may bestored on a computer-readable storage medium or in a computing system.In some embodiments, these software modules may configure a computingsystem to perform one or more of the exemplary embodiments disclosedherein.

In addition, one or more of the modules described herein may transformdata, physical devices, and/or representations of physical devices fromone form to another. For example, one or more of the modules recitedherein may transform a computing device by tuning a dynamic analysisbased on a static analysis.

The preceding description has been provided to enable others skilled inthe art to best utilize various aspects of the exemplary embodimentsdisclosed herein. This exemplary description is not intended to beexhaustive or to be limited to any precise form disclosed. Manymodifications and variations are possible without departing from thespirit and scope of the instant disclosure. The embodiments disclosedherein should be considered in all respects illustrative and notrestrictive. Reference should be made to the appended claims and theirequivalents in determining the scope of the instant disclosure.

Unless otherwise noted, the terms “a” or “an,” as used in thespecification and claims, are to be construed as meaning “at least oneof.” In addition, for ease of use, the words “including” and “having,”as used in the specification and claims, are interchangeable with andhave the same meaning as the word “comprising.”

What is claimed is:
 1. A computer-implemented method for combiningstatic and dynamic code analysis, at least a portion of the method beingperformed by a computing system comprising at least one computerprocessor, the method comprising: identifying, as part of a process forevaluating executable code for compliance with at least one data lossprevention policy, executable code that is to be analyzed to determinewhether the executable code is capable of leaking sensitive data;performing a static analysis of the executable code to identify one ormore objects comprising at least one inter-process communication channelwhich the executable code may use to transfer sensitive data between twoor more software applications that use the at least one inter-processcommunication channel; using a result of the static analysis to tune adynamic analysis by instrumenting the executable code to track access tothe one or more objects identified during the static analysis;performing the dynamic analysis by, while the executable code is beingexecuted, tracking the one or more objects identified during the staticanalysis to determine whether the executable code leaks sensitive datavia the one or more objects identified during the static analysis. 2.The computer-implemented method of claim 1, wherein: the one or moreobjects identified during the static analysis comprise at least onestorage location; instrumenting the executable code comprises monitoringdata written to and read from the at least one storage location.
 3. Thecomputer-implemented method of claim 2, wherein the at least one storagelocation comprises at least one of: a file; a database; a DALVICbytecode content provider.
 4. The computer-implemented method of claim1, wherein: the executable code comprises: a first software applicationthat can access sensitive data; and a second software application thatcan transmit sensitive data outside a computing system that hosts thefirst software application and the second software application;identifying the executable code comprises identifying the inter-processcommunications channel that the first software application may use totransfer sensitive data to the second software application;instrumenting the executable code comprises tracking sensitive datatransferred between the first software application and the secondsoftware application using the inter-process communications channel. 5.The computer-implemented method of claim 1, wherein the at least oneinter-process communication channel comprises at least one of: a namedpipe; a message passing; synchronization; shared memory; a copy andpaste function; a clipboard; a remote procedure call.
 6. Thecomputer-implemented method of claim 1, wherein identifying theexecutable code comprises at least one of: identifying the executablecode during development of the executable code; identifying theexecutable code as part of a process for evaluating the executable codewithin a particular computing environment; identifying the executablecode while the executable code is running.
 7. The computer-implementedmethod of claim 1, wherein the at least one data loss prevention policyis configured to prevent sensitive information from leaking.
 8. A systemfor combining static and dynamic code analysis, the system comprising:an identification module programmed to identify, as part of a processfor evaluating executable code for compliance with at least onedata-loss prevention policy, executable code that is to be analyzed todetermine whether the executable code is capable of leaking sensitivedata; a static analyzer programmed to perform a static analysis of theexecutable code to identify one or more objects comprising at least oneinter-process communication channel which the executable code may use totransfer sensitive data between two or more software applications thatuse the at least one inter-process communication channel; a tuningmodule programmed to use a result of the static analysis to tune adynamic analysis by instrumenting the executable code to track access tothe one or more objects identified during the static analysis; a dynamicanalyzer programmed to perform the dynamic analysis by, while theexecutable code is being executed, tracking the one or more objectsidentified during the static analysis; at least one computer processorconfigured to execute the identification module, the static analyzer,the tuning module, and the dynamic analyzer.
 9. The system of claim 8,wherein: the executable code comprises a single software application;the one or more objects identified during the static analysis compriseobjects to which the single software application may write to and readfrom.
 10. The system of claim 8, wherein: the one or more objectsidentified during the static analysis comprise at least one storagelocation; the tuning module instruments the executable code bymonitoring data written to and read from the storage locations.
 11. Thesystem of claim 8, wherein: the executable code comprises a plurality ofsoftware applications; the one or more objects identified during thestatic analysis comprise one or more storage locations that eachsoftware application within the plurality of software applications mayaccess.
 12. The system of claim 8, wherein: the executable codecomprises a plurality of software applications; the one or more objectsidentified during the static analysis comprise one or more inter-processcommunication channels that may transfer sensitive information betweentwo or more software applications within the plurality of softwareapplications.
 13. The system of claim 8, wherein: the executable codecomprises: a first software application that can access sensitive data;and a second software application that can transmit sensitive dataoutside a computing system that hosts the first software application andthe second software application; the identification module identifiesthe executable code at least in part by identifying the inter-processcommunications channel that the first software application may use totransfer sensitive data to the second software application; the tuningmodule instruments the executable code at least in part by trackingsensitive data transferred between the first software application andthe second software application using the inter-process communicationschannel.
 14. The system of claim 8, wherein the tuning moduleinstruments the executable code by at least one of: inserting analysiscode into the executable code inline; using static binaryinstrumentation to instrument the executable code before the executablecode is run; using dynamic binary instrumentation to inject analysiscode into the executable code while the executable code is running. 15.A non-transitory computer-readable medium comprising one or morecomputer-executable instructions that, when executed by at least oneprocessor of a computing device, cause the computing device to:identify, as part of a process for evaluating executable code forcompliance with at least one data-loss prevention policy, executablecode that is to be analyzed to determine whether the executable code iscapable of leaking sensitive data; perform a static analysis of theexecutable code to identify one or more objects comprising at least oneinter-process communication channel which the executable code may use totransfer sensitive data between two or more software applications thatuse the at least one inter-process communication channel; use a resultof the static analysis to tune a dynamic analysis by instrumenting theexecutable code to track access to the one or more objects identifiedduring the static analysis; perform the dynamic analysis by, while theexecutable code is being executed, tracking the one or more objectsidentified during the static analysis to determine whether theexecutable code leaks sensitive data via the one or more objectsidentified during the static analysis.
 16. The non-transitorycomputer-readable medium of claim 15, wherein: the one or more objectsidentified during the static analysis comprise at least one storagelocation; the one or more computer-executable instructions instrumentthe executable code by monitoring data written to and read from the atleast one storage location.
 17. The non-transitory computer-readablemedium of claim 15, wherein the one or more computer-executableinstructions further perform the static analysis by at least one of:performing a data-flow analysis to gather information relating to theexecutable code; using a control flow graph of the executable code todetermine parts of the executable code to which a particular valueassigned to a variable potentially propagates.
 18. The non-transitorycomputer-readable medium of claim 15, wherein the one or morecomputer-executable instructions identify the executable code by:identifying a first software application that is capable of accessingsensitive data; identifying a second software application that iscapable of transferring the sensitive data outside a computing systemcomprising the second software application, wherein the executable codecomprises the first and second software application.
 19. Thenon-transitory computer-readable medium of claim 18, further comprising:identifying the executable code at least in part by identifying theinter-process communications channel that the first software applicationmay use to transfer sensitive data to the second software application;instrumenting the executable code at least in part by tracking sensitivedata transferred between the first software application and the secondsoftware application using the inter-process communications channel. 20.The non-transitory computer-readable medium of claim 15, wherein theexecutable code comprises at least one of: JAVA bytecode; DALVIKbytecode.